Development Engineer

Join a team focused on advancing demand forecasting capabilities that support digital fulfillment operations and help improve planning across multiple channels. This remote opportunity is ideal for a strong Python and ML engineering professional who enjoys scaling data science work into reliable, production-ready systems.

Responsibilities

• Build and maintain machine learning pipelines that support forecasting workflows from data preparation through deployment
• Scale pandas-based processes into PySpark and other distributed frameworks for large-volume processing
• Develop and optimize data pipelines with an emphasis on performance, reliability, and cost efficiency
• Support model training, validation, experimentation, and versioned deployment in production environments
• Work with analytical data stores and manage dataset design, partitioning, clustering, and validation practices
• Contribute to workflow orchestration using tools such as Kubeflow Pipelines, Vertex AI, or Airflow
• Collaborate with data scientists and platform engineers to productionize forecasting solutions
• Refactor, extend, and improve existing codebases while following sound software engineering practices
• Support CI/CD, testing, dependency management, and code quality processes for ML systems
• Help modernize forecasting infrastructure used to support store operations planning and customer experience

Skills

• Strong Python programming skills with experience writing production-quality code
• Hands-on machine learning and data science experience, including building and deploying ML models
• Experience with time series forecasting methods such as Prophet, ARIMA, or similar approaches
• Ability to convert pandas workflows to PySpark for large-scale data processing
• Experience with distributed data processing tools such as Spark, Dask, or Ray
• Knowledge of hyperparameter tuning, model validation, and experiment tracking
• Familiarity with feature engineering and feature store concepts
• Experience with BigQuery or similar analytical databases
• Working knowledge of Git, testing frameworks such as pytest, and code quality tools
• Understanding of cloud platforms such as GCP, including storage and ML services
• Experience with Docker, Kubernetes, and CI/CD workflows

Preferred Skills

• Experience with Ray for distributed training or inference
• Exposure to Hadoop ecosystem tools such as Hive or HDFS
• Knowledge of model monitoring and drift detection practices
• Familiarity with infrastructure-as-code tools such as Terraform
• Background in retail, supply chain, or demand forecasting environments
• Experience helping data science teams turn research code into scalable production solutions
• Comfort working in a collaborative, cross-functional environment
• Strong problem-solving skills and a continuous improvement mindset

Horizontal is committed to fostering an inclusive environment where different perspectives, backgrounds, and experiences are valued. We welcome candidates who bring curiosity, collaboration, and a shared commitment to building equitable and respectful workplaces.

By applying for this position, you acknowledge and agree that Horizontal Talent may contact you regarding your application using automated technology, including phone calls, SMS/text messages, or email, which may be delivered by our virtual AI recruiter, Alex.

Please apply through this online posting or by visiting our Job Board at Applications will be accepted for 4 weeks. For those that join the team, we offer competitive compensation and benefits including medical, dental, vision, and retirement. Check out all we have to offer and how you can become part of the Horizontal Talent Team. The pay range for this role is $49 - $85 per hour based on qualifications and experience.